Machine learning in the cloud: 5 cloud tools to harness artificial intelligence for your business

Machine learning in the cloud: 5 cloud tools to harness artificial intelligence for your business

Machine learning in the cloud: Amazon Web Services

AWS launched its Amazon Machine Learning service in Europe this week, with the aim of making it easier for developers of all skill levels to access complex algorithms.

AWS says its machine learning service can generate billions of predictions a day, tapping into AWS data from services such as RedShift, S3 and its Relational Database Service.

Machine learning in the cloud: Microsoft Azure

The AWS service goes up against Microsoft’s own machine learning offering, part of its Azure cloud. Again the Azure Machine Learning tool – launched earlier this year – is aimed at simplifying access to analytics tools.

The cloud service allows developers to add machine learning functions into applications they build – such as fraud detection, social network analysis or sentiment analysis – using drag and drop tools in its Machine Learning Studio.

Machine learning in the cloud: Google Prediction API

Google was one of the first to provide machine learning capabilities via the cloud a few years ago with its Prediction API, allowing customers to tap the search giant’s machine learning algorithms to analyse data and predict future outcomes.

Machine learning in the cloud: Alibaba’s Aliyun

This week, Chinese ecommerce giant Alibaba announced that its cloud computing business, Aliyun, would offer an artificial intelligence service to help enterprise customers streamline analytics software development.

The service is based on Aliyun’s Open Data Processing Service (ODPS) technology, which is capable of processing 100 petabytes of data in six hours.

The DT PAI platform offers a drag and drop interface to simplify the process for developers.

“What used to take days can be completed in minutes,” said Xiao Wei, senior product expert with Alibaba’s cloud business, as the service was announced.

Machine learning in the cloud: IBM Watson Analytics

The Watson Analytics cloud service was unveiled last year as part of IBM’s plans to turn Watson from a part-time game show contestant into a bona fide enterprise software proposition.

It aims to help organisations that have little or no experience of predictive analytics put their business data to good use.

IBM had already launched its Watson Developer Cloud – in 2013 – offering access to APIs via its Bluemix platform as a service cloud, allowing developers to create their own applications based on Watson’s smarts.

Machine learning in the cloud: BigML

It is not only big IT firms that are moving into artificial intelligence in the cloud. BigML is one of a number of startups in the market.

Founded in Oregon in 2011, BigML offers a simple user interface, allowing users to upload data sets to start making predictions.

Machine learning in the cloud: Wise.io

Another startup firm, Wise.io also aims to democratise the use of machine learning. Its algorithms were initially developed to helps astronomers discover and map new stars, before being put to use by businesses.

Machine learning in the cloud: Amazon Web Services

AWS launched its Amazon Machine Learning service in Europe this week, with the aim of making it easier for developers of all skill levels to access complex algorithms.

AWS says its machine learning service can generate billions of predictions a day, tapping into AWS data from services such as RedShift, S3 and its Relational Database Service.